#Filter matlab 2008 code

The syntax for creating different types of IIR filters In MATLAB, we can design various IIF filters like Butterworth, Chebyshev, and Bessel.

#Filter matlab 2008 code

Original Filtered Code Sine Wave Code %% Visualization close all % Close all open figures alpha = 0.25 % Filter factor of 1/4 f_s = 10000 % 10 kHz sample frequency f_1 = 300 % First sine wave with a frequency of 300 Hz f_2 = 2500 % Second sine wave with a frequency of 2.5 kHz samples = 100 % Calculate/plot 100 samples n = linspace ( 0 ,samples- 1 ,samples) % Generate a vector with sample numbers t = n / f_s % Generate a vector with time sine_1 = sin ( 2 * pi *f_1*t) % Calculate the (sampled) sine waves sine_2 = sin ( 2 * pi *f_2*t) signal = (sine_1 + sine_2) % Mix the two sine waves together b = alpha % Coefficients of the numerator of the transfer function a = % Coefficients of the denominator of the transfer function filtered = filter (b,a,signal) % Filter the signal oversample_continuous = 20 % Create a version with ten times more samples % to display the smooth, continuous signal samples_continuous = oversample_continuous * samples n_continuous = linspace ( 0, samples_continuous- 1 ,samples_continuous) / oversample_continuous t_continuous = n_continuous / f_s sine_1_continuous = sin ( 2 * pi *f_1*t_continuous) sine_2_continuous = sin ( 2 * pi *f_2*t_continuous) signal_continuous = (sine_1_continuous + sine_2_continuous) % Plot the two original sine waves figure ( 'pos' ,) hold on plot (t_continuous, sine_1_continuous, 'k' ) plot (t_continuous, sine_2_continuous, 'k' ) title ( 'Original sine waves' ) xlabel ( 'Time (s)' ) ylabel ( 'Amplitude' ) % Plot the continuous signal, the sampled version and the filtered output figure ( 'pos' ,) hold on plot (n_continuous, signal_continuous, 'k' ) plot (n, signal, 'o' ) plot (n, filtered, '-o' ) title ( 'Filtering the signal' ) xlabel ( 'Sample' ) ylabel ( 'Amplitude' ) legend ( 'Original signal', 'Sampled signal', 'Filtered signal' ) % Apply a fast fourier transform and plot the spectra of the % original signal and of the filtered output figure ( 'pos' ,) hold on f = linspace ( 0 ,samples- 1 ,samples)*f_s/samples original_spectrum = ( abs ( fft (signal))* 2 /samples).^2 filtered_spectrum = ( abs ( fft (filtered))* 2 /samples).^2 plot (f( 1 : 1 +samples/ 2 ),original_spectrum( 1 : 1 +samples/ 2 ), '-o' ) plot (f( 1 : 1 +samples/ 2 ),filtered_spectrum( 1 : 1 +samples/ 2 ), '-o' ) title ( 'Power spectral density' ) xlabel ( 'Frequency (Hz)' ) legend ( 'Original signal', 'Filtered signal' ) % Calculate the attenuation of the two sine waves f_1_index = f_1*samples/f_s+ 1 A_1 = filtered_spectrum(f_1_index) / original_spectrum(f_1_index) A_1_dB = 10 * log10 (A_1) fprintf ( 'Attenuation of first sine wave ( %.0f Hz) = %.02f dB ', f_1, A_1_dB) f_2_index = f_2*samples/f_s+ 1 A_2 = filtered_spectrum(f_2_index) / original_spectrum(f_2_index) A_2_dB = 10 * log10 (A_2) fprintf ( 'Attenuation of second sine wave ( %.0f Hz) = %.02f dB ', f_2, A_2_dB) % Open the filter visualization tool fvtool (b,a, 'Fs' ,f_s) %% WAV export samples = f_s* 2 % 2 seconds of audio n = linspace ( 0 ,samples- 1 ,samples) % Generate a vector with sample numbers t = n / f_s % Generate a vector with time sine_1 = sin ( 2 * pi *f_1*t) % Calculate the (sampled) sine waves sine_2 = sin ( 2 * pi *f_2*t) signal = (sine_1 + sine_2)/ 2 % Mix the two sine waves together filtered = filter ( alpha ,signal) % Filter the signal audiowrite( 'original.wav' ,signal,f_s) % Export as audio audiowrite( 'filtered.wav' ,filtered,f_s) Audio Code = audioread( 'telegraph_road_original.wav' ) alpha = 0.25 % Filter factor of 1/4 b = alpha % Coefficients of the numerator of the transfer function a = % Coefficients of the denominator of the transfer function filtered = filter (b,a,signal) % Filter the signal audiowrite( 'telegraph_road_filtered.Hadoop, Data Science, Statistics & others Home get_app feedback Filtering in MATLAB Pieter P Simple Finite Impulse Response Notch Filter.Discretization of a Fourth-Order Butterworth Filter.DTLTI Systems, Transfer Functions, and the Z-transform.Flashing the ESP8266 with an Arduino UNO.Compiling Optiboot - ATmega328P at custom frequency.

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